#pragma once

#include <random>
#include <stdint.h>

#include "rocksdb_benchmark_namespace.h"

namespace ROCKSDB_BENCHMARK_NAMESPACE {
// A very simple random number generator.  Not especially good at
// generating truly random bits, but good enough for our needs in this
// package.
class Random {
private:
    enum : uint32_t {
        M = 2147483647L // 2^31-1
    };
    enum : uint64_t {
        A = 16807 // bits 14, 8, 7, 5, 2, 1, 0
    };

    uint32_t seed_;
    int64_t tmp;

    static uint32_t GoodSeed(uint32_t s) { return (s & M) != 0 ? (s & M) : 1; }

public:
    // This is the largest value that can be returned from Next()
    enum : uint32_t { kMaxNext = M };

    explicit Random(uint32_t s)
        : seed_(GoodSeed(s))
    {
    }

    void Reset(uint32_t s) { seed_ = GoodSeed(s); }

    uint32_t Next()
    {
        // We are computing
        //       seed_ = (seed_ * A) % M,    where M = 2^31-1
        //
        // seed_ must not be zero or M, or else all subsequent computed values
        // will be zero or M respectively.  For all other values, seed_ will end
        // up cycling through every number in [1,M-1]
        uint64_t product = seed_ * A;

        // Compute (product % M) using the fact that ((x << 31) % M) == x.
        seed_ = static_cast<uint32_t>((product >> 31) + (product & M));
        // The first reduction may overflow by 1 bit, so we may need to
        // repeat.  mod == M is not possible; using > allows the faster
        // sign-bit-based test.
        if (seed_ > M) {
            seed_ -= M;
        }
        return seed_;
    }

    // Returns a uniformly distributed value in the range [0..n-1]
    // REQUIRES: n > 0
    uint32_t Uniform(int n) { return Next() % n; }

    // Randomly returns true ~"1/n" of the time, and false otherwise.
    // REQUIRES: n > 0
    bool OneIn(int n) { return Uniform(n) == 0; }

    // "Optional" one-in-n, where 0 or negative always returns false
    // (may or may not consume a random value)
    bool OneInOpt(int n) { return n > 0 && OneIn(n); }

    // Returns random bool that is true for the given percentage of
    // calls on average. Zero or less is always false and 100 or more
    // is always true (may or may not consume a random value)
    bool PercentTrue(int percentage)
    {
        return static_cast<int>(Uniform(100)) < percentage;
    }

    // Skewed: pick "base" uniformly from range [0,max_log] and then
    // return "base" random bits.  The effect is to pick a number in the
    // range [0,2^max_log-1] with exponential bias towards smaller numbers.
    uint32_t Skewed(int max_log)
    {
        return Uniform(1 << Uniform(max_log + 1));
    }

    // Returns a Random instance for use by the current thread without
    // additional locking
    static Random* GetTLSInstance();
};

// A good 32-bit random number generator based on std::mt19937.
// This exists in part to avoid compiler variance in warning about coercing
// uint_fast32_t from mt19937 to uint32_t.
class Random32 {
private:
    std::mt19937 generator_;

public:
    explicit Random32(uint32_t s)
        : generator_(s)
    {
    }

    // Generates the next random number
    uint32_t Next() { return static_cast<uint32_t>(generator_()); }

    // Returns a uniformly distributed value in the range [0..n-1]
    // REQUIRES: n > 0
    uint32_t Uniform(uint32_t n)
    {
        return static_cast<uint32_t>(
            std::uniform_int_distribution<std::mt19937::result_type>(
                0, n - 1)(generator_));
    }

    // Returns an *almost* uniformly distributed value in the range [0..n-1].
    // Much faster than Uniform().
    // REQUIRES: n > 0
    uint32_t Uniformish(uint32_t n)
    {
        // fastrange (without the header)
        return static_cast<uint32_t>((uint64_t(generator_()) * uint64_t(n)) >> 32);
    }

    // Randomly returns true ~"1/n" of the time, and false otherwise.
    // REQUIRES: n > 0
    bool OneIn(uint32_t n) { return Uniform(n) == 0; }

    // Skewed: pick "base" uniformly from range [0,max_log] and then
    // return "base" random bits.  The effect is to pick a number in the
    // range [0,2^max_log-1] with exponential bias towards smaller numbers.
    uint32_t Skewed(int max_log)
    {
        return Uniform(uint32_t{ 1 } << Uniform(max_log + 1));
    }

    // Reset the seed of the generator to the given value
    void Seed(uint32_t new_seed) { generator_.seed(new_seed); }
};

// A good 64-bit random number generator based on std::mt19937_64
class Random64 {
private:
    std::mt19937_64 generator_;

public:
    explicit Random64(uint64_t s)
        : generator_(s)
    {
    }

    // Generates the next random number
    uint64_t Next() { return generator_(); }

    // Returns a uniformly distributed value in the range [0..n-1]
    // REQUIRES: n > 0
    uint64_t Uniform(uint64_t n)
    {
        return std::uniform_int_distribution<uint64_t>(0, n - 1)(generator_);
    }

    // Randomly returns true ~"1/n" of the time, and false otherwise.
    // REQUIRES: n > 0
    bool OneIn(uint64_t n) { return Uniform(n) == 0; }

    // Skewed: pick "base" uniformly from range [0,max_log] and then
    // return "base" random bits.  The effect is to pick a number in the
    // range [0,2^max_log-1] with exponential bias towards smaller numbers.
    uint64_t Skewed(int max_log)
    {
        return Uniform(uint64_t(1) << Uniform(max_log + 1));
    }
};
}
